Alzheimer's disease (AD), the most common cause of dementia in older adults, is a major public health concern affecting approximately 5 million adults over the age of 65 in the United States. Developing methods to assess and identify individuals prior to the onset of significant clinical symptoms is crucial to extending the quality of life in individuals with AD and their caregivers. However, specific biological markers that predict cognitive decline in older adults remain elusive. One approach to identifying potential markers of preclinical AD is to examine brain function in individuals at higher risk of developing the disease, such as those diagnosed with Mild Cognitive Impairment (MCI). MCI generally implies impairment on tests of cognitive function, but maintenance of intact global cognition and daily functioning levels. Recent definitions of MCI characterize clinical subtypes of individuals with primary memory impairments (amnestic) or primary non-memory impairments (non-amnestic) involving one or more cognitive areas. However, the lack of a universal operational definition of MCI among clinical and research practices results in widely varying prevalence rates and progression rates from MCI to AD. Additional factors, such as cerebrovascular function, may also influence progression of MCI and AD. The current proposal seeks to evaluate the relationship between cerebrovascular function as measured by cerebral blood flow (CBF), brain function as measured by the blood-oxygenation level dependent (BOLD) response, and cognition in older adults with amnestic and non-amnestic MCI, as well as a group of cognitively intact older adults. In addition, two types of MCI criteria will be used to compare the consistency of functional brain profiles between different MCI classification schemes. Using a novel neuroimaging technique that simultaneously measures CBF and BOLD response, this study will examine functional activation patterns in MCI during episodic memory performance, one of the first major cognitive functions to decline in AD. This is an important method because differences in the BOLD response may also reflect variations in cerebrovascular functioning that become more pronounced with age or disease and can be confused with neural activity. Further, this study plans to examine the influence of cerebrovascular disease risk on CBF and BOLD response in MCI to reveal the interaction between MCI and vascular risk factors. Overall, the proposed study will better characterize the neurovascular underpinnings of the MCI subtypes and the influence that cerebrovascular function has on brain function in these individuals. This study will provide information to better identify individuals at higher risk for AD so that effective treatment strategies can be implemented at an early stage and will assess factors that may modify the progression of MCI to AD. As even small delays in the onset of AD are predicted to significantly reduce the global burden of this disease, a better understanding of the factors that interact to increase risk are imperative to improve the lives of individuals in our rapidly aging society.